1. Field of the Invention
Embodiments of the invention generally relate to techniques for the analysis and/or monitoring of data networks, and more particularly, analyzing the performance of networks for various applications. Specifically, various embodiments described herein are directed to determining edge effects occurring within a network based upon end-to-end performance measurements.
2. Description of the Background Art
The ongoing improvements in the reliability, performance, and cost-effectiveness of modern data networks are motivating a demand for their use in a variety of communication applications. This success has contributed to the increasing size and complexity of the data networks, as well as the expectation among their users for consistently high levels of quality when using sophisticated applications, such as, for example, Voice over Internet Protocol (VoIP) telephony and/or video communications. Given the complexity and dynamic nature of these networks, assessing and monitoring the network's performance can present a number of challenges. Network engineers designing and running networks may utilize data collection and analysis tools to assess Quality-of-Service (QoS) measures such as packet loss rates, delays, and jitter, and for doing network bandwidth calculations. This information can be utilized for several reasons, such as: monitoring network performance and utilization over time; drilling into problems and finding their causes; detecting congestion; planning capacity and network provisioning; and for ensuring compliance with service level agreements.
Such data collection and analytical tools are especially useful with real-time applications that require high and sustained levels of quality, such as, for example, VoIP, video streaming, video-conferencing, and/or on-line games. Determining the performance of networks for such real-time applications can be challenging for a variety of reasons. Once such reason is that the size of network can limit the type of analyses that can be performed in practice. Another reason is that networks are evolving entities and QoS characteristics can change rapidly, for example, as a result of load or as a result of an automatic process that is attempting to circumvent some local network problem. Yet another reason is that network engineers often do not have access to all the relevant components in the network, for example, a node within a network may belong to a different administrative domain, or a network segment can belong to an Internet Service Provider.
Traditional approaches to network analysis have relied on detailed queuing models at the individual router level. However, such “local” modeling may not adequately capture the complexities and dynamic behavior of modern networks, including the fact that end-to-end results can be affected by interactions between adjacent and non-adjacent network components. Expanding such local models to incorporate the behavior of even a moderately sized network may be impractical because of the very large number of potential interactions.
Accordingly, it would be beneficial to apply improved network analysis and/or monitoring techniques for locating problems within a network and quickly assessing the network's performance at a detailed level.